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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Column() changed from object to string in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 183, in _generate_tables
                  df = pandas_read_json(f)
                       ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1391, in _parse
                  self.obj = DataFrame(
                             ^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/core/frame.py", line 778, in __init__
                  mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
                  return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
                  index = _extract_index(arrays)
                          ^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 677, in _extract_index
                  raise ValueError("All arrays must be of the same length")
              ValueError: All arrays must be of the same length
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3608, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2368, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2573, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2082, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 544, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 383, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 186, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
                  pa_table = paj.read_json(
                             ^^^^^^^^^^^^^^
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0

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FABDEM V1.2 STAC Catalog

Dataset Description

FABDEM (Forest And Buildings removed Copernicus DEM) is a global elevation dataset that provides a comprehensive 30-meter resolution digital elevation model with building and tree height biases systematically removed from the Copernicus GLO 30 Digital Elevation Model (DEM). This enhanced dataset offers more accurate representation of bare-earth topography for hydrological modeling, flood risk assessment, and other geospatial applications where vegetation and built infrastructure can introduce significant elevation errors.

Dataset Summary

  • Resolution: 30 meters
  • Coverage: Global
  • Format: GeoTIFF tiles organized in STAC (SpatioTemporal Asset Catalog) format
  • Total Items: 19,013 tiles
  • Tile Coverage: Approximately 1° × 1° per tile
  • Version: 1.2
  • Data Type: Float32 elevation values in meters
  • Coordinate Reference System: WGS84 (EPSG:4326)

Source and Development

This dataset has been developed by the University of Bristol as part of research published in Environmental Research Letters. The methodology removes vegetation and building heights from the original Copernicus DEM using machine learning techniques and auxiliary datasets, resulting in a more accurate representation of underlying terrain elevations.

Dataset Structure

The catalog is organized hierarchically to facilitate efficient data discovery and access:

fabdem-v12/
├── catalog.json (root catalog)
├── tiles/
|   ├── N00E000-N10E010_FABDEM_V1-2/...
|   └── ...
├── stac_catalog/
│   ├── catalog.json (root catalog)
|   ├── N01E001_FABDEM_V1-2/...
|   └── ...

Each tile follows the naming convention and covers approximately 1 degree of latitude and longitude, with tiles grouped into 10° × 10° regional folders mirroring the original data distribution structure.

Key Features

  • STAC Compliance: Fully compliant with STAC specification for interoperability
  • On-demand Access: Eliminates need to download large ZIP archives

Usage

For detailed usage examples, refer to the included notebook stac_catalog_query.ipynb.

Data Quality and Limitations

  • Accuracy: Improved accuracy over original Copernicus DEM, particularly in forested and urban areas
  • Temporal Snapshot: Represents conditions circa 2020
  • Processing Artifacts: Some processing artifacts may remain in complex terrain
  • Polar Regions: Coverage limitations in extreme polar regions following Copernicus DEM constraints

Technical Specifications

Provenance and Attribution

This STAC catalog implementation is inspired by the work at https://github.com/cordmaur/fabdem-brazil-south and provides improved accessibility to the original FABDEM dataset distributed by the University of Bristol.

Original Data Source: https://data.bris.ac.uk/data/dataset/s5hqmjcdj8yo2ibzi9b4ew3sn

Citation: When using this dataset, please cite the original research paper and acknowledge the data source.

License and Terms of Use

Please refer to the original data distribution terms at the University of Bristol repository.

References

Hawker, Laurence, Peter Uhe, Luntadila Paulo, Jeison Sosa, James Savage, Christopher Sampson, and Jeffrey Neal. "A 30 m Global Map of Elevation with Forests and Buildings Removed." Environmental Research Letters 17, no. 2 (February 2022): 024016. https://doi.org/10.1088/1748-9326/ac4d4f.

Contact and Support

For questions about the original dataset methodology and creation, contact the University of Bristol research team. For issues specific to this STAC catalog implementation, please refer to the repository documentation and issue tracker.

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